https://github.com/solrikk/cripto-boats
CryptoBoat is an advanced cryptocurrency trading bot powered by artificial intelligence. It combines LSTM neural networks and Random Forest algorithms to make intelligent trading decisions in the cryptocurrency futures market.
https://github.com/solrikk/cripto-boats
ai aitrade aitraderbot bybit bybit-api bybit-trader cripto lstm-model money trade trade-bot tradeai trading trading-algorithms trading-api trading-strategies
Last synced: 6 months ago
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CryptoBoat is an advanced cryptocurrency trading bot powered by artificial intelligence. It combines LSTM neural networks and Random Forest algorithms to make intelligent trading decisions in the cryptocurrency futures market.
- Host: GitHub
- URL: https://github.com/solrikk/cripto-boats
- Owner: Solrikk
- License: mit
- Created: 2024-10-27T20:21:58.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-09T14:37:48.000Z (10 months ago)
- Last Synced: 2025-03-25T11:49:11.992Z (10 months ago)
- Topics: ai, aitrade, aitraderbot, bybit, bybit-api, bybit-trader, cripto, lstm-model, money, trade, trade-bot, tradeai, trading, trading-algorithms, trading-api, trading-strategies
- Language: Python
- Homepage:
- Size: 3.58 MB
- Stars: 15
- Watchers: 5
- Forks: 8
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
-----------------
## ⚠️ IMPORTANT DISCLAIMER ⚠️
### This trading bot is currently in EXPERIMENTAL/BETA testing phase. By using this software:
1. **Cryptocurrency Trading Risks:** You acknowledge that trading cryptocurrencies involves substantial risks, including the potential loss of your invested capital.
2. **Technological Limitations:** The bot utilizes Artificial Intelligence and Machine Learning (AI/ML) models that are still undergoing testing and improvements. This may lead to unforeseen errors or inaccurate signals.
3. **Liability for Losses:** You accept full responsibility for any financial losses that may occur as a result of using this bot.
4. **No Guarantee of Performance:** Past performance does not guarantee future results. The cryptocurrency market is highly volatile and can change rapidly.
5. **Capital Management:** Trade only with funds you can afford to lose. Do not invest money that is necessary for your living expenses or other essential purposes.
6. **No Financial Advice:** This software is NOT financial advice. Use it at your own risk and consult with professional financial advisors before making investment decisions.
## Support the Project 💖
If you've found this project helpful or profitable, consider supporting its development:
Code - **bc1q80hqj3crwysc5nwd6u8pzc6lrsau6peuvrz6te**
Your donations help maintain and improve the project, ensuring its continued development and enhancement.
# Small-Boats 🚀
----
## Overview 📊
**CryptoBoat** is a **semi-automated cryptocurrency trading system** that emphasizes manual control over key trading decisions while managing multiple positions simultaneously. Unlike fully automated bots, this strategy allows you to:
[](https://visitorbadge.io/status?path=https%3A%2F%2Fgithub.com%2FSolrikk%2FSmall-Boats)
[](https://github.com/Solrikk/Small-Boats/stargazers)
[](https://github.com/Solrikk)
[](https://github.com/Solrikk/Small-Boats/blob/main/LICENSE)
[](https://www.python.org)
[](https://fastapi.tiangolo.com)
- Manually control Take-Profit and Stop-Loss levels
- Open multiple strategic positions across different assets
- Benefit from risk diversification through position spreading
- Offset potential losses with gains from other positions
## Technical Details 🔧
### AI Models Used
1. **LSTM (Long Short-Term Memory)**
- Specialized neural network for time series prediction
- Capable of learning long-term dependencies
- Optimized for cryptocurrency price movement patterns
- Uses multiple technical indicators for enhanced accuracy
2. **Random Forest**
- Ensemble learning algorithm
- Combines multiple decision trees
- Reduces overfitting through aggregation
- Provides robust market trend predictions
### Technical Indicators
- RSI (Relative Strength Index)
- EMA (Exponential Moving Average)
- MACD (Moving Average Convergence Divergence)
- Bollinger Bands
- Ichimoku Cloud
- VWAP (Volume Weighted Average Price)
- ATR (Average True Range)
## Performance Features 🎯
- Real-time market data processing
- Multi-timeframe analysis
- Advanced risk management system
- Position size optimization
- Automated entry/exit signals
- Portfolio rebalancing
- Custom indicator combinations
## Technical Architecture 🔧
### System Components
1. **Neural Networks**
- LSTM Network: 2-layer bidirectional architecture
- Input shape: (60, 18) - 60 timeframes, 18 features
- Hidden layers: 100 units each with dropout (0.3)
- Output: Binary classification (buy/sell signal)
2. **Random Forest Classifier**
- Ensemble of 100 decision trees
- Feature flattening: 1080 dimensions (60 timeframes × 18 features)
- Class balancing with SMOTE
- Parallel prediction processing
3. **Technical Indicators**
- Price-based: EMA, Bollinger Bands, Ichimoku
- Momentum: RSI, MACD, Stochastic
- Volume: VWAP
- Volatility: ATR
## Installation & Setup 🛠️
### Prerequisites
- Python 3.8+
- GPU recommended for faster model training
- Minimum 4GB RAM
- Bybit account with API access
### Step-by-Step Installation
1. **Initialize Project:**
```bash
git clone https://github.com/Solrikk/CryptoBoat.git
cd CryptoBoat
```
2. **Install Required Packages:**
```bash
pip install numpy pandas tensorflow scikit-learn ta ccxt matplotlib
```
3. **Configure Exchange:**
Update `main.py` with your Bybit API credentials:
```python
API_KEY = "your_api_key" # From Bybit dashboard
API_SECRET = "your_api_secret"
```
4. **Configure Risk Parameters:**
In `main.py`, adjust trading parameters:
```python
risk_percentage = 0.3 # Risk per trade (0.3%)
TRADE_COOLDOWN = 60 # Seconds between trades
```
### Running the Bot
1. **Initial Launch:**
```bash
python main.py
```
2. **Monitor Operations:**
- Check `trading_bot_derivatives.log` for real-time status
- Review `trades_log.json` for trade history
### System Architecture
```
Input Data → Feature Engineering → Model Prediction → Trading Logic
↓ ↓ ↓ ↓
OHLCV Data → Technical Indicators → LSTM + RF → Position Management
```
### Performance Monitoring
- Log files track all operations
- Real-time balance updates
- Trade execution confirmations
- Error handling and reporting
### Risk Management
- Position sizing based on account balance
- Maximum risk per trade: 0.3%
- Trade cooldown period: 60 seconds
- Automatic error recovery
- Multiple validation layers
### Error Handling
- Network disconnect protection
- API error recovery
- Invalid data detection
- Balance verification
- Order validation
## Usage Guide 📚
1. Start the Bot:
```bash
python main.py
```
2. Monitor the Logs:
- Check `trading_bot_derivatives.log` for detailed operation logs
- Review trade history in `trades_log.json`
3. Configure Risk Parameters:
- Adjust position sizes in `calculate_position_size()`
- Modify risk percentage (default: 0.3%)
- Set custom stop-loss levels
⚠️ **Remember**: Past performance does not guarantee future results. Always trade responsibly and within your risk tolerance.
## Community & Support 🤝
- Join our community discussions
- Share your trading strategies
- Report issues and suggest improvements
- Help others get started